Electroencephalography (“EEG”), which involves recording electrical activity along the scalp, is a valuable tool in detecting and monitoring for a host of neurological disorders. For example, by comparing the recorded electrical activity (e.g., voltage fluctuations) in a brain of a subject to the physical manifestations (e.g., a seizure) observed in the subject, a practitioner may diagnosis the particular neurological disorder (e.g., epilepsy). However, even if EEG and video data is readily available, the practitioner still faces the hurdle of identifying what physical manifestations correspond to what electrical activity. This process is further complicated by the fact that in addition to observing a subject for the slightest physical manifestation (e.g., a movement of a finger, a blink of an eye, a twitch of a lip, etc.), the practitioner must simultaneously review numerous channels of incoming EEG data for millisecond fluctuations, any of which may affect an eventual diagnosis.